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 程式師世界 >> 編程語言 >> C語言 >> C++ >> C++入門知識 >> opencv 人臉識別 (一)訓練樣本的處理,opencv人臉

opencv 人臉識別 (一)訓練樣本的處理,opencv人臉

編輯:C++入門知識

opencv 人臉識別 (一)訓練樣本的處理,opencv人臉


本文實現基於eigenface的人臉檢測與識別。給定一個圖像數據庫,進行以下步驟:

  • 進行人臉檢測,將檢測出的人臉存入數據庫2
  • 對數據庫2進行人臉建模
  • 在測試集上進行recognition
本篇實現第一步:
  • 進行人臉檢測,將檢測出的人臉存入數據庫2

環境:vs2010+opencv 2.4.6.0

特征:LBP

Input:一個人臉數據庫,15個人,每人20個樣本(左右)。

Output:人臉檢測,並識別出每張檢測到的人臉。

===============================

本文完成第一步,數據預處理:自動檢測所有文件夾中每個sample中的人臉,作為訓練數據。

Input:一個color文件夾,每個文件夾中有1~N這N個子文件夾,每個子文件夾內有n張包括第n類人的照片,如圖。

最終結果:

核心:face detection(detectAndDraw)

輔助:截圖並保存部分圖片(CutImg),文件夾內圖片遍歷(read_img),圖片轉換成相同大小(normalizeone)

括號內分別是函數名,下面分別給出代碼及說明。

1. 遍歷文件夾:CBrowseDir類和CStatDir類(具體見這篇),三個文件如下:

1.1 BrowseDir.h

#pragma once
#include "direct.h"
#include "string.h"
#include "io.h"
#include "stdio.h" 
#include 
#include 
using namespace std;
class CBrowseDir
{
protected:
  char m_szInitDir[_MAX_PATH];

public:
  CBrowseDir();
  bool SetInitDir(const char *dir);
  bool BeginBrowse(const char *filespec);
  vector<char*> BeginBrowseFilenames(const char *filespec);

protected:
  bool BrowseDir(const char *dir,const char *filespec);
  vector<char*> GetDirFilenames(const char *dir,const char *filespec);
  virtual bool ProcessFile(const char *filename);
  virtual void ProcessDir(const char *currentdir,const char *parentdir);
};

1.2 BrowseDir.cpp

#include "BrowseDir.h"
#include "direct.h"
#include "string.h"
#include "io.h"
#include "stdio.h" 
#include 
#include 
using namespace std;

CBrowseDir::CBrowseDir()
{
  getcwd(m_szInitDir,_MAX_PATH);
  int len=strlen(m_szInitDir);
  if (m_szInitDir[len-1] != '\\')
    strcat(m_szInitDir,"\\");
}

bool CBrowseDir::SetInitDir(const char *dir)
{
  if (_fullpath(m_szInitDir,dir,_MAX_PATH) == NULL)
    return false;

  if (_chdir(m_szInitDir) != 0)
    return false;
  int len=strlen(m_szInitDir);
  if (m_szInitDir[len-1] != '\\')
    strcat(m_szInitDir,"\\");

  return true;
}

vector<char*>CBrowseDir:: BeginBrowseFilenames(const char *filespec)
{
  ProcessDir(m_szInitDir,NULL);
  return GetDirFilenames(m_szInitDir,filespec);
}

bool CBrowseDir::BeginBrowse(const char *filespec)
{
  ProcessDir(m_szInitDir,NULL);
  return BrowseDir(m_szInitDir,filespec);
}

bool CBrowseDir::BrowseDir(const char *dir,const char *filespec)
{
  _chdir(dir);
  long hFile;
  _finddata_t fileinfo;
  if ((hFile=_findfirst(filespec,&fileinfo)) != -1)
  {
    do
    {
      if (!(fileinfo.attrib & _A_SUBDIR))
      {
        char filename[_MAX_PATH];
        strcpy(filename,dir);
        strcat(filename,fileinfo.name);
        cout << filename << endl;
        if (!ProcessFile(filename))
          return false;
      }
    } while (_findnext(hFile,&fileinfo) == 0);
    _findclose(hFile);
  }
  _chdir(dir);
  if ((hFile=_findfirst("*.*",&fileinfo)) != -1)
  {
    do
    {
      if ((fileinfo.attrib & _A_SUBDIR))
      {
        if (strcmp(fileinfo.name,".") != 0 && strcmp
          (fileinfo.name,"..") != 0)
        {
          char subdir[_MAX_PATH];
          strcpy(subdir,dir);
          strcat(subdir,fileinfo.name);
          strcat(subdir,"\\");
          ProcessDir(subdir,dir);
          if (!BrowseDir(subdir,filespec))
            return false;
        }
      }
    } while (_findnext(hFile,&fileinfo) == 0);
    _findclose(hFile);
  }
  return true;
}

vector<char*> CBrowseDir::GetDirFilenames(const char *dir,const char *filespec)
{
  _chdir(dir);
  vector<char*>filename_vec;
  filename_vec.clear();

  long hFile;
  _finddata_t fileinfo;
  if ((hFile=_findfirst(filespec,&fileinfo)) != -1)
  {
    do
    {
      if (!(fileinfo.attrib & _A_SUBDIR))
      {
        char *filename = new char[_MAX_PATH];
        strcpy(filename,dir);
        //int st = 0;	while (dir[st++]!='\0');
        strcat(filename,fileinfo.name); //filename[st]='\0';
        filename_vec.push_back(filename);
      }
    } while (_findnext(hFile,&fileinfo) == 0);
    _findclose(hFile);
  }
  _chdir(dir);
  if ((hFile=_findfirst("*.*",&fileinfo)) != -1)
  {
    do
    {
      if ((fileinfo.attrib & _A_SUBDIR))
      {
        if (strcmp(fileinfo.name,".") != 0 && strcmp
          (fileinfo.name,"..") != 0)
        {
          char subdir[_MAX_PATH];
          strcpy(subdir,dir);
          strcat(subdir,fileinfo.name);
          strcat(subdir,"\\");
          ProcessDir(subdir,dir);
          return GetDirFilenames(subdir,filespec);
        }
      }
    } while (_findnext(hFile,&fileinfo) == 0);
    _findclose(hFile);
  }
  return filename_vec;
}

bool CBrowseDir::ProcessFile(const char *filename)
{
  return true;
}

void CBrowseDir::ProcessDir(const char 
  *currentdir,const char *parentdir)
{
}

1.3 StatDir.h

#pragma once
#include "browsedir.h"
class CStatDir:public CBrowseDir
{
protected:
  int m_nFileCount;   //保存文件個數
  int m_nSubdirCount; //保存子目錄個數

public:
  CStatDir()
  {
    m_nFileCount=m_nSubdirCount=0;
  }

  int GetFileCount()
  {
    return m_nFileCount;
  }

  int GetSubdirCount()
  {
    return m_nSubdirCount-1;
  }

protected:
  virtual bool ProcessFile(const char *filename)
  {
    m_nFileCount++;
    return CBrowseDir::ProcessFile(filename);
  }

  virtual void ProcessDir
    (const char *currentdir,const char *parentdir)
  {
    m_nSubdirCount++;
    CBrowseDir::ProcessDir(currentdir,parentdir);
  }
};

2. 輔助函數Prehelper.h, Prehelper.cpp:負責返回文件夾內所有圖片(read_img),檢測人臉(detectAndDraw並可以在原圖中畫出),截圖(CutImg),提取(DetectandExtract)

2.1 Prehelper.h

//preprocessing helper
//@ Author : Rachel-Zhang

#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/contrib/contrib.hpp"
#include 
#include 
#include 
using namespace cv;
using namespace std;

void normalizeone(const char* dir,IplImage* standard);

void CutImg(IplImage* src, CvRect rect,IplImage* res);

vector detectAndDraw( Mat& img, CascadeClassifier& cascade,
  CascadeClassifier& nestedCascade,
  double scale, bool tryflip,bool draw );

IplImage* DetectandExtract(Mat& img, CascadeClassifier& cascade,
  CascadeClassifier& nestedCascade,
  double scale, bool tryflip);

int read_img(const string& dir, vector &images);

vector<pair<char*,mat>>  read_img(const string& dir);

2.2 Prehelper.cpp

#include "Prehelper.h"
#include "BrowseDir.h"
#include "StatDir.h"

#include 
#include 
#include 
using namespace cv;

void normalizeone(const char* dir,IplImage* standard)
{
  CStatDir statdir;
  if (!statdir.SetInitDir(dir))
  {
    puts("Dir not exist");
    return;
  }
  vector<char*>file_vec = statdir.BeginBrowseFilenames("*.*");
  int i;
  for (i=0;i<file_vec.size();i++) {="" iplimage*="" cur_img="cvLoadImage(file_vec[i],CV_LOAD_IMAGE_GRAYSCALE);" iplimage*cur_gray="cvCreateImage(cvGetSize(cur_img),cur_img-">depth,1);
    cvResize(cur_img,standard,CV_INTER_AREA);
    //cvCvtColor(standard,cur_gray,CV_RGB2GRAY);
    // 		cvNamedWindow("cur_img",CV_WINDOW_AUTOSIZE);
    // 		cvNamedWindow("standard",CV_WINDOW_AUTOSIZE);
    // 		cvShowImage("cur_img",cur_img);
    // 		cvShowImage("standard",standard);
    // 		cvWaitKey();
    cvSaveImage(file_vec[i],cur_img);
  }
}

void CutImg(IplImage* src, CvRect rect,IplImage* res)
{
  CvSize imgsize;
  imgsize.height = rect.height;
  imgsize.width = rect.width;
  cvSetImageROI(src,rect);
  cvCopy(src,res);
  cvResetImageROI(res);
}

int read_img(const string& dir, vector &images)
{
  CStatDir statdir;
  if (!statdir.SetInitDir(dir.c_str()))
  {
    cout<<"Direct "<<dir<<" not="" exist!"<<endl;="" return="" 0;="" }="" int="" cls_id="dir[dir.length()-1]-'0';" vector<char*="">file_vec = statdir.BeginBrowseFilenames("*.*");
  int i,s = file_vec.size();
  for (i=0;i<s;i++) {="" mat="" graymat="imread(file_vec[i],0);" graymat.reshape(1,1);="" flatten="" to="" row="" images.push_back(graymat);="" }="" return="" s;="" vector<pair<char*,mat="">>  read_img(const string& dir)
{
  CStatDir statdir;
  pair<char*,mat> pfi;
  vector<pair<char*,mat>> Vp;
  if (!statdir.SetInitDir(dir.c_str()))
  {
    cout<<"Direct "<<dir<<" not="" exist!"<<endl;="" return="" vp;="" }="" int="" cls_id="dir[dir.length()-1]-'0';" vector<char*="">file_vec = statdir.BeginBrowseFilenames("*.*");
  int i,s = file_vec.size();
  for (i=0;i<s;i++) {="" pfi.first="file_vec[i];" pfi.second="imread(file_vec[i]);" vp.push_back(pfi);="" }="" return="" vp;="" vector<rect=""> detectAndDraw( Mat& img, CascadeClassifier& cascade,
  CascadeClassifier& nestedCascade,
  double scale, bool tryflip, bool draw )
{
  int i = 0;
  double t = 0;
  vector faces, faces2;
  const static Scalar colors[] =  { CV_RGB(0,0,255),
    CV_RGB(0,128,255),
    CV_RGB(0,255,255),
    CV_RGB(0,255,0),
    CV_RGB(255,128,0),
    CV_RGB(255,255,0),
    CV_RGB(255,0,0),
    CV_RGB(255,0,255)} ;
  Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );

  cvtColor( img, gray, CV_BGR2GRAY );
  resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
  equalizeHist( smallImg, smallImg );

  t = (double)cvGetTickCount();
  cascade.detectMultiScale( smallImg, faces,
    1.1, 2, 0
    |CV_HAAR_FIND_BIGGEST_OBJECT
    //|CV_HAAR_DO_ROUGH_SEARCH
    //|CV_HAAR_SCALE_IMAGE
    ,
    Size(30, 30) );
  if( tryflip )
  {
    flip(smallImg, smallImg, 1);
    cascade.detectMultiScale( smallImg, faces2,
      1.1, 2, 0
      |CV_HAAR_FIND_BIGGEST_OBJECT
      //|CV_HAAR_DO_ROUGH_SEARCH
      //|CV_HAAR_SCALE_IMAGE
      ,
      Size(30, 30) );
    for( vector::const_iterator r = faces2.begin(); r != faces2.end(); r++ )
    {
      faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));
    }
  }
  t = (double)cvGetTickCount() - t;
  printf( "detection time = %g ms\n", t/((double)cvGetTickFrequency()*1000.) );
  if(draw)
  {
    for( vector::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
    {
      Mat smallImgROI;
      vector nestedObjects;
      Point center;
      Scalar color = colors[i%8];
      int radius;

      double aspect_ratio = (double)r->width/r->height;
      rectangle( img, cvPoint(cvRound(r->x*scale), cvRound(r->y*scale)),
        cvPoint(cvRound((r->x + r->width-1)*scale), cvRound((r->y + r->height-1)*scale)),
        color, 3, 8, 0);
      if( nestedCascade.empty() )
        continue;
      smallImgROI = smallImg(*r);
      nestedCascade.detectMultiScale( smallImgROI, nestedObjects,
        1.1, 2, 0
        |CV_HAAR_FIND_BIGGEST_OBJECT
        //|CV_HAAR_DO_ROUGH_SEARCH
        //|CV_HAAR_DO_CANNY_PRUNING
        //|CV_HAAR_SCALE_IMAGE
        ,
        Size(30, 30) );
      //draw eyes
      //         for( vector::const_iterator nr = nestedObjects.begin(); nr != nestedObjects.end(); nr++ )
      //         {
      //             center.x = cvRound((r->x + nr->x + nr->width*0.5)*scale);
      //             center.y = cvRound((r->y + nr->y + nr->height*0.5)*scale);
      //             radius = cvRound((nr->width + nr->height)*0.25*scale);
      //             circle( img, center, radius, color, 3, 8, 0 );
      //         }
    }
    cv::imshow( "result", img );
  }
  return faces;
}

IplImage* DetectandExtract(Mat& img, CascadeClassifier& cascade,
  CascadeClassifier& nestedCascade,
  double scale, bool tryflip)
{
  vector Rvec = detectAndDraw(img,cascade,nestedCascade,scale,tryflip,0);
  int i,maxxsize=0,id=-1,area;
  for (i=0;i<rvec.size();i++) {="" area="Rvec[i].width*Rvec[i].height;" if(maxxsize<area)="" maxxsize="area;" id="i;" }="" iplimage*="" transimg="cvCloneImage(&(IplImage)img);" if(id!="-1)" cvsize="" imgsize;="" imgsize.height="Rvec[id].height;" imgsize.width="Rvec[id].width;" res="cvCreateImage(imgsize,transimg-">depth,transimg->nChannels);
    CutImg(transimg,Rvec[id],res);

    return res;
  }
  return NULL;
}

3. 主函數

//Detect.cpp
//Preprocessing - Detect, Cut and Save
//@Author : Rachel-Zhang

#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"

#include 
#include 
#include 
#include 
#include "BrowseDir.h"
#include "StatDir.h"
#include "Prehelper.h"

using namespace std;
using namespace cv;
#define CAM 2
#define PHO 1
#define K 5

string cascadeName = "E:/software/opencv2.4.6.0/data/haarcascades/haarcascade_frontalface_alt.xml";
string nestedCascadeName = "E:/software/opencv2.4.6.0/data/haarcascades/haarcascade_eye_tree_eyeglasses.xml";

int main( )
{
  CvCapture* capture = 0;
  Mat frame, frameCopy, image;
  string inputName;
  bool tryflip = false;
  int mode;
  CascadeClassifier cascade, nestedCascade; 
  double scale = 1.0;
  if( !cascade.load( cascadeName ) ||!nestedCascade.load( nestedCascadeName))
  {
    cerr << "ERROR: Could not load classifier cascade or nestedCascade" << endl;//若出現該問題請去檢查cascadeName,可能是opencv版本路徑問題
    return -1;
  }

// 	printf("select the mode of detection: \n1: from picture\t 2: from camera\n");
// 	scanf("%d",&mode);
  char** pics = (char**) malloc(sizeof*pics);

  /************************************************************************/
  /*                                  detect face and save                                    */
  /************************************************************************/
  int i,j;
  cout<<"detect and save..."<<endl; const="" char="" dir[256]="D:\\Face_recognition\\pic\\" ;="" string="" cur_dir;="" id[5];="" for(i="1;" i<="K;" i++)="" {="" cur_dir="dir;" _itoa(i,id,10);="" cur_dir.append("color\\");="" cur_dir.append(id);="" vector<pair<char*,mat="">> imgs=read_img(cur_dir);
    for(j=0;j<imgs.size();j++) {="" iplimage*="" res="DetectandExtract(imgs[j].second,cascade,nestedCascade,scale,tryflip);" if(res)="" cvsaveimage(imgs[j].first,res);="" }="" return="" 0;="" }<="" pre="">

正確的輸出就是一系列人臉檢測時間,且原文件夾內的圖片變成了檢測出的人臉(如上面結果圖所示)。

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